{"id":7790,"date":"2022-07-20T15:30:17","date_gmt":"2022-07-20T13:30:17","guid":{"rendered":"https:\/\/guide-gnss.com\/?page_id=7790"},"modified":"2024-10-15T13:24:41","modified_gmt":"2024-10-15T11:24:41","slug":"mesures-validees","status":"publish","type":"page","link":"https:\/\/guide-gnss.com\/fr\/mesures-validees\/","title":{"rendered":"Mesures GNSS valid\u00e9es"},"content":{"rendered":"<p>[et_pb_section fb_built=\u00a0\u00bb1&Prime; fullwidth=\u00a0\u00bbon\u00a0\u00bb _builder_version=\u00a0\u00bb4.16&Prime; saved_tabs=\u00a0\u00bball\u00a0\u00bb global_colors_info=\u00a0\u00bb{}\u00a0\u00bb][et_pb_fullwidth_header title=\u00a0\u00bbMesures GNSS et de Capteurs sous Accr\u00e9ditation\u00a0\u00bb _builder_version=\u00a0\u00bb4.16&Prime; title_font=\u00a0\u00bbMontserrat|700|||||||\u00a0\u00bb title_text_align=\u00a0\u00bbcenter\u00a0\u00bb title_font_size=\u00a0\u00bb32px\u00a0\u00bb title_letter_spacing=\u00a0\u00bb3px\u00a0\u00bb subhead_font=\u00a0\u00bbMontserrat|600|||||||\u00a0\u00bb subhead_text_align=\u00a0\u00bbcenter\u00a0\u00bb subhead_font_size=\u00a0\u00bb20px\u00a0\u00bb use_background_color_gradient=\u00a0\u00bbon\u00a0\u00bb background_color_gradient_stops=\u00a0\u00bb#375882 0%|#4370a0 100%\u00a0\u00bb background_color_gradient_start=\u00a0\u00bb#375882&Prime; background_color_gradient_end=\u00a0\u00bb#4370a0&Prime; custom_padding=\u00a0\u00bb||27px|||\u00a0\u00bb global_colors_info=\u00a0\u00bb{}\u00a0\u00bb]<\/p>\n<h2 style=\"text-align: center; font-size: 20px;\"><span style=\"font-family: 'Calibri Light',sans-serif;\"><b>Production massive de donn\u00e9es pour des op\u00e9rations d\u2019apprentissage de r\u00e9seaux de neurones ( Deep-Learning )<\/b><\/span><\/h2>\n<p>[\/et_pb_fullwidth_header][\/et_pb_section][et_pb_section fb_built=\u00a0\u00bb1&Prime; _builder_version=\u00a0\u00bb4.16&Prime; custom_padding=\u00a0\u00bb5px||50px||false|false\u00a0\u00bb global_colors_info=\u00a0\u00bb{}\u00a0\u00bb][et_pb_row column_structure=\u00a0\u00bb1_2,1_2&Prime; _builder_version=\u00a0\u00bb4.16&Prime; custom_margin=\u00a0\u00bb40px|auto||auto||\u00a0\u00bb custom_padding=\u00a0\u00bb0px||20px||false|false\u00a0\u00bb global_colors_info=\u00a0\u00bb{}\u00a0\u00bb][et_pb_column type=\u00a0\u00bb1_2&Prime; _builder_version=\u00a0\u00bb4.16&Prime; global_colors_info=\u00a0\u00bb{}\u00a0\u00bb][et_pb_text _builder_version=\u00a0\u00bb4.16&Prime; _module_preset=\u00a0\u00bbdefault\u00a0\u00bb custom_padding=\u00a0\u00bb0px|||||\u00a0\u00bb global_colors_info=\u00a0\u00bb{}\u00a0\u00bb]<\/p>\n<h2>d\u00e9finition<\/h2>\n<p style=\"text-align: justify;\">Les int\u00e9grateurs de syst\u00e8mes de positionnement ont souvent besoin de d\u00e9velopper leurs propres algorithmes de fusion. Des donn\u00e9es r\u00e9elles, collect\u00e9es sur le terrain, sont n\u00e9cessaires pour coupler les capteurs avec le r\u00e9cepteur GNSS. Ces mesures de capteur et ces signaux GNSS doivent \u00eatre parfaitement repr\u00e9sentatifs des conditions d&rsquo;usage consid\u00e9r\u00e9es.<span style=\"font-weight: 400;\"><\/span><\/p>\n<p style=\"text-align: justify;\">Les \u00e9carts dans les mesures de position, caus\u00e9s par les perturbations de l&rsquo;environnement, sont \u00e0 att\u00e9nuer \u00e0 l&rsquo;aide de m\u00e9thodes d&rsquo;hybridation. Ces techniques am\u00e9liorent les performances du syst\u00e8me, tant sur ses capacit\u00e9s de r\u00e9silience, de reconvergence sur les bonnes positions, que sur ses propres capacit\u00e9s d&rsquo;auto-estimation des erreurs.<\/p>\n<p style=\"text-align: justify;\">A dessein, des technologies de deep-learning sont de plus en plus souvent impl\u00e9ment\u00e9es pour entrainer des filtres de navigation.<\/p>\n<p style=\"text-align: justify;\">Dans tous les cas, la collecte des donn\u00e9es d&rsquo;essais est une op\u00e9ration incontournable o\u00f9 il faut autant de jeux de donn\u00e9es que de profils d&rsquo;erreurs \u00e0 surmonter. Dans certains cas, un m\u00eame mesurage peut renvoyer un ensemble de mesures diff\u00e9rentes les unes des autres. Ces jeux de donn\u00e9es se multiplient pour chacun des capteurs ou des r\u00e9cepteurs utilis\u00e9s.<\/p>\n<p style=\"text-align: justify;\">Dans ce contexte, la production massive de donn\u00e9es est \u00e9galement un r\u00e9el d\u00e9fi pour obtenir des r\u00e9sultats exploitables.<span style=\"font-weight: 400;\"><\/span><\/p>\n<p>&nbsp;<\/p>\n<p>[\/et_pb_text][\/et_pb_column][et_pb_column type=\u00a0\u00bb1_2&Prime; _builder_version=\u00a0\u00bb4.16&Prime; global_colors_info=\u00a0\u00bb{}\u00a0\u00bb][et_pb_image src=\u00a0\u00bbhttps:\/\/guide-gnss.com\/wp-content\/uploads\/2024\/01\/240124-leurrage-3.jpg\u00a0\u00bb title_text=\u00a0\u00bbIA pour l&rsquo;apprentissage automatique GNSS\u00a0\u00bb _builder_version=\u00a0\u00bb4.21.0&Prime; _module_preset=\u00a0\u00bbdefault\u00a0\u00bb hover_enabled=\u00a0\u00bb0&Prime; global_colors_info=\u00a0\u00bb{}\u00a0\u00bb alt=\u00a0\u00bbIA pour l&rsquo;apprentissage automatique GNSS\u00a0\u00bb sticky_enabled=\u00a0\u00bb0&Prime;][\/et_pb_image][et_pb_image src=\u00a0\u00bbhttps:\/\/guide-gnss.com\/wp-content\/uploads\/2022\/11\/Dispersion-of-measurements.jpg\u00a0\u00bb title_text=\u00a0\u00bbmesures de position GNSS\u00a0\u00bb _builder_version=\u00a0\u00bb4.21.0&Prime; _module_preset=\u00a0\u00bbdefault\u00a0\u00bb hover_enabled=\u00a0\u00bb0&Prime; global_colors_info=\u00a0\u00bb{}\u00a0\u00bb alt=\u00a0\u00bbDispersion of measurements &#8211; GNSS Test Lab\u00a0\u00bb sticky_enabled=\u00a0\u00bb0&Prime;][\/et_pb_image][et_pb_text _builder_version=\u00a0\u00bb4.21.0&Prime; text_font_size=\u00a0\u00bb10px\u00a0\u00bb hover_enabled=\u00a0\u00bb0&Prime; locked=\u00a0\u00bboff\u00a0\u00bb global_colors_info=\u00a0\u00bb{}\u00a0\u00bb sticky_enabled=\u00a0\u00bb0&Prime;]<\/p>\n<p style=\"text-align: center;\">Figure 1a \u2013 \u00ab IA pour l&rsquo;apprentissage automatique GNSS \u00bb<br \/>Figure 1b\u2013 \u00ab Dispersion GNSS des positions \u00bb<\/p>\n<p>[\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row column_structure=\u00a0\u00bb1_2,1_2&Prime; _builder_version=\u00a0\u00bb4.16&Prime; custom_margin=\u00a0\u00bb40px|auto||auto||\u00a0\u00bb custom_padding=\u00a0\u00bb0px||20px||false|false\u00a0\u00bb global_colors_info=\u00a0\u00bb{}\u00a0\u00bb][et_pb_column type=\u00a0\u00bb1_2&Prime; _builder_version=\u00a0\u00bb4.16&Prime; global_colors_info=\u00a0\u00bb{}\u00a0\u00bb][et_pb_text _builder_version=\u00a0\u00bb4.16&Prime; _module_preset=\u00a0\u00bbdefault\u00a0\u00bb custom_padding=\u00a0\u00bb0px|||||\u00a0\u00bb global_colors_info=\u00a0\u00bb{}\u00a0\u00bb]<\/p>\n<h2>crit\u00e8res de performance<\/h2>\n<p style=\"text-align: justify;\">Les algorithmes de Deep Learning sont une voie de recherche prometteuse dans l&rsquo;extraction automatis\u00e9e des donn\u00e9es complexes. Une bonne mise en \u0153uvre de ces techniques fera gagner un temps pr\u00e9cieux en R&amp;D.<span style=\"font-weight: 400;\"><\/span><\/p>\n<p style=\"text-align: justify;\">Leurs capacit\u00e9s de pr\u00e9diction sont subordonn\u00e9es \u00e0 la pertinence des op\u00e9rations d&rsquo;apprentissage et \u00e0 la qualit\u00e9 des mesures soumises aux filtres d&rsquo;apprentissage.<\/p>\n<p style=\"text-align: justify;\">En particulier, ces donn\u00e9es doivent \u00eatre \u00e0 la fois :<\/p>\n<ul>\n<li style=\"text-align: justify;\">Coh\u00e9rentes et int\u00e8gres<\/li>\n<li style=\"text-align: justify;\">Compl\u00e8tes et nettoy\u00e9es<\/li>\n<li style=\"text-align: justify;\">Et en quantit\u00e9 suffisante<\/li>\n<\/ul>\n<p>La strat\u00e9gie d&rsquo;apprentissage doit \u00eatre pens\u00e9e en amont, c&rsquo;est \u00e0 dire d\u00e8s les sp\u00e9cifications d&rsquo;essais.<\/p>\n<p>&nbsp;<\/p>\n<p>[\/et_pb_text][\/et_pb_column][et_pb_column type=\u00a0\u00bb1_2&Prime; _builder_version=\u00a0\u00bb4.16&Prime; global_colors_info=\u00a0\u00bb{}\u00a0\u00bb][et_pb_image src=\u00a0\u00bbhttps:\/\/guide-gnss.com\/wp-content\/uploads\/2022\/10\/IME-IA-4.jpg\u00a0\u00bb title_text=\u00a0\u00bbHybridation GNSS -m\u00e9thode de test\u00a0\u00bb show_in_lightbox=\u00a0\u00bbon\u00a0\u00bb _builder_version=\u00a0\u00bb4.21.0&Prime; _module_preset=\u00a0\u00bbdefault\u00a0\u00bb hover_enabled=\u00a0\u00bb0&Prime; global_colors_info=\u00a0\u00bb{}\u00a0\u00bb alt=\u00a0\u00bbIME IA &#8211; GNSS application\u00a0\u00bb sticky_enabled=\u00a0\u00bb0&Prime;][\/et_pb_image][et_pb_text _builder_version=\u00a0\u00bb4.21.0&Prime; text_font_size=\u00a0\u00bb10px\u00a0\u00bb hover_enabled=\u00a0\u00bb0&Prime; locked=\u00a0\u00bboff\u00a0\u00bb global_colors_info=\u00a0\u00bb{}\u00a0\u00bb sticky_enabled=\u00a0\u00bb0&Prime;]<\/p>\n<p style=\"text-align: center;\">Figure 2 \u2013 \u00ab Hybridation GNSS \u2013 M\u00e9thode de test \u00bb<\/p>\n<p>[\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row column_structure=\u00a0\u00bb1_2,1_2&Prime; _builder_version=\u00a0\u00bb4.16&Prime; custom_margin=\u00a0\u00bb40px|auto||auto||\u00a0\u00bb custom_padding=\u00a0\u00bb0px||20px||false|false\u00a0\u00bb global_colors_info=\u00a0\u00bb{}\u00a0\u00bb][et_pb_column type=\u00a0\u00bb1_2&Prime; _builder_version=\u00a0\u00bb4.16&Prime; global_colors_info=\u00a0\u00bb{}\u00a0\u00bb][et_pb_text _builder_version=\u00a0\u00bb4.16&Prime; _module_preset=\u00a0\u00bbdefault\u00a0\u00bb custom_padding=\u00a0\u00bb0px|||||\u00a0\u00bb global_colors_info=\u00a0\u00bb{}\u00a0\u00bb]<\/p>\n<h2>MOYENS DE M\u00c9TROLOGIE<\/h2>\n<p style=\"text-align: justify;\">GUIDE est un laboratoire d&rsquo;essais accr\u00e9dit\u00e9. En l\u2019occurrence, notre laboratoire a les comp\u00e9tences, l&rsquo;instrumentation et des m\u00e9thodes valid\u00e9es pour fournir massivement les donn\u00e9es certifi\u00e9es, attendues pour impl\u00e9menter des processus de deep-learning.<span style=\"font-weight: 400;\"><\/span><\/p>\n<p style=\"text-align: justify;\">Cette prestation est une simple extension de ses activit\u00e9s d&rsquo;ing\u00e9nierie d&rsquo;essais. Les mesures produites lors des essais sont destin\u00e9es \u00e0 une \u00e9quipe de R&amp;D au lieu d&rsquo;\u00eatre analys\u00e9es par les \u00e9quipes de GUIDE en vue d&rsquo;une \u00e9valuation de performances.<\/p>\n<p style=\"text-align: justify;\">Le succ\u00e8s d&rsquo;une op\u00e9ration d&rsquo;apprentissage r\u00e9side, en premier lieu, dans la coh\u00e9rence des donn\u00e9es \u00e0 collecter, c&rsquo;est-\u00e0-dire la qualit\u00e9 des sp\u00e9cifications d&rsquo;essais. Toutes les autres t\u00e2ches d\u00e9couleront de cette premi\u00e8re \u00e9tape.<\/p>\n<p>[\/et_pb_text][\/et_pb_column][et_pb_column type=\u00a0\u00bb1_2&Prime; _builder_version=\u00a0\u00bb4.16&Prime; global_colors_info=\u00a0\u00bb{}\u00a0\u00bb][et_pb_image src=\u00a0\u00bbhttps:\/\/guide-gnss.com\/wp-content\/uploads\/2022\/07\/Moyens-de-metrologie.jpg\u00a0\u00bb title_text=\u00a0\u00bbMoyens de m\u00e9trologie GNSS\u00a0\u00bb _builder_version=\u00a0\u00bb4.16&Prime; _module_preset=\u00a0\u00bbdefault\u00a0\u00bb global_colors_info=\u00a0\u00bb{}\u00a0\u00bb][\/et_pb_image][et_pb_text _builder_version=\u00a0\u00bb4.21.0&Prime; text_font_size=\u00a0\u00bb10px\u00a0\u00bb hover_enabled=\u00a0\u00bb0&Prime; locked=\u00a0\u00bboff\u00a0\u00bb global_colors_info=\u00a0\u00bb{}\u00a0\u00bb sticky_enabled=\u00a0\u00bb0&Prime;]<\/p>\n<p style=\"text-align: center;\"><em>Figure 3 &#8211; Banc d&rsquo;essai dans le laboratoire GUIDE<\/em><\/p>\n<p>[\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=\u00a0\u00bb4.21.0&Prime; _module_preset=\u00a0\u00bbdefault\u00a0\u00bb global_colors_info=\u00a0\u00bb{}\u00a0\u00bb][et_pb_column type=\u00a0\u00bb4_4&Prime; _builder_version=\u00a0\u00bb4.21.0&Prime; _module_preset=\u00a0\u00bbdefault\u00a0\u00bb global_colors_info=\u00a0\u00bb{}\u00a0\u00bb][et_pb_button button_url=\u00a0\u00bbhttps:\/\/guide-gnss.com\/fr\/ingenierie-des-moyens-essais\/\u00a0\u00bb button_text=\u00a0\u00bbIng\u00e9nierie des moyens d&rsquo;essais\u00a0\u00bb button_alignment=\u00a0\u00bbcenter\u00a0\u00bb _builder_version=\u00a0\u00bb4.21.0&Prime; _module_preset=\u00a0\u00bbdefault\u00a0\u00bb global_colors_info=\u00a0\u00bb{}\u00a0\u00bb][\/et_pb_button][\/et_pb_column][\/et_pb_row][\/et_pb_section]<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Production massive de donn\u00e9es pour des op\u00e9rations d\u2019apprentissage de r\u00e9seaux de neurones ( Deep-Learning )d\u00e9finition Les int\u00e9grateurs de syst\u00e8mes de positionnement ont souvent besoin de d\u00e9velopper leurs propres algorithmes de fusion. Des donn\u00e9es r\u00e9elles, collect\u00e9es sur le terrain, sont n\u00e9cessaires pour coupler les capteurs avec le r\u00e9cepteur GNSS. Ces mesures de capteur et ces signaux [&hellip;]<\/p>\n","protected":false},"author":5,"featured_media":7804,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":"","_et_gb_content_width":""},"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v20.11 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Mesures GNSS valid\u00e9es - GUIDE GNSS<\/title>\n<meta name=\"description\" content=\"Mesures GNSS valid\u00e9es. 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